Research SDE - Machine Learning at Microsoft

Research SDE - Machine Learning Details

Nov. 6, 2018, 5:35 p.m.
Individual Contributor
Redmond, WA
company, this team The Microsoft Applied
From being able to log you in with face recognition, launch Cortana with a voice command, to the exciting possibilities in augmented reality, are you itching to play a part in bringing applications of computer vision to millions? The Microsoft Applied Sciences Group incubates disruptive technologies for Microsoft's next-gen hardware products and is working on several exciting projects that will shape how computers and other devices perceive the user and the user's environment. Operating as a startup within the company, this team works closely with several research and product teams to bring compelling new experiences to the market. A lot of these experiences will be powered by speech and computer vision – and as part of this team, you will have the unique opportunity to work on almost every aspect of a shipping audio and vision system: camera optics, sensors, data pipeline and of course, developing and implementing the algorithms that make magic happen!

We are looking for an audio, speech and/or computer vision researcher with expertise in deep learning techniques to help our devices compute better understanding of the user and the environment. The ability to analyze multimodal sensor data and interpret various human and human-object interactions is key to Applied Sciences' mission of enabling a seamless set of human computer interactions. As part of this team, you will be working with a growing team of talented researchers already dedicated to this mission and use data and hardware only available to a select few. Naturally, the opportunity for
Requirements: BS in Computer Science, Electrical Engineering, or related field. Strong knowledge on Computer Science and Signal Processing and ability to understand and implement complex algorithms. Expertise in deep learning techniques (RNN's, CNN's, LSTM, reinforcement learning) Strong publication record in top-tier audio/speech/vision conferences (ICASSP, InterSpeech, CVPR, ECCV, ICCV) and journals is a plus. Familiarity with Python research stack (Numpy, Matplotlib, Jupyter, OpenCV) is a plus TensorFlow, Caffe, Torch, CNTK experience is a plus
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